Aging and Health Financing in the US: A General Equilibrium Analysis Juergen Jung Chung Tran Towson University Australian National University Matthew Chambers Towson University Barcelona GSE Summer Forum, June 2016
Disclaimer This project was supported by funds from the Centers for Medicare & Medicaid Services, Office of the Actuary (CMS/OACT). The content is solely the responsibility of the authors and does not represent the official views of the funding institutions.
Health Spending by Financing Source 12 10 Other Worker's compensation State insurance 8 Federal insurance in $1,000 Tricare 6 CHAMPUS Veteran's benefits Private insurance 4 Medicaid Medicare 2 Out-of-pocket 0 20 30 40 50 60 70 80 90 Age Source: MEPS 1999-2009
Population > 65 (in % of Working Age Population) 30 25 20 15 % 10 5 0 2010 2020 2030 2040 2050 2060 Decade
Source: Boards of Trustees (2015)
Comments The long-term fiscal outlook in the US Sensitive to assumptions about how health care spending (CBO (2014)) Fiscal gap between 6.1 percent and 9.0 percent of GDP (Auerbach and Gale (2013)) CBO’s projections abstract from microfoundations of health spending and financing Lifecycle profiles of health-related behavior Behavioral responses to demographic shift and policy reforms
This paper 1 Quantify the effects of population aging on healthcare spending and financing in US 2 Assess the implications of the ACA reform in this aging context
How? A Bewley-Grossman model of health capital with heterogenous agents idiosyncratic income and health shocks incomplete markets Microfoundations of health-related behavior demand for medical services and health insurance The US institutional details: Medicare and Medicaid Group-based (GHI) and Individual-based insurance (IHI) Calibrate the model to US data before the ACA reform Medical Expenditure Panel Survey Population projections by CMS/OACT
Results 1 Without ACA: Aging leads to large increases in medical spending ↑ Health expenditures by 37 percent (2060 demographic structure) ↑ Medicare by 50 percent ↑ Insurance take-up for workers from 77 to 81 percent 2 Introduction of ACA increases the fraction of insured workers up to 99 percent expansion of Medicaid and IHI ACA stabilizes insurance take-up for all simulated periods mitigates the increase in health expenditures ↓ health expenditures by 2 percent move uninsured workers into Medicaid increases fiscal cost mainly via the expansion of Medicaid aging itself diminishes impact of ACA
Related Literature 1 Economics of aging Wise (2005), Bloom, Canning and Fink (2010) and De la Croix (2013) for an overview Aging and fiscal policy: Deterministic: Auerbach and Kotlikoff (1987), Faruqee (2002), Kotlikoff, Smetters and Walliser (2007) Stochastic: De Nardi, Imrohoroğlu and Sargent (1999), Braun and Joines (2015), Kitao (2015) and Nishiyama (2015) 2 Quantitative macroeconomics/public finance Pioneers: Bewley (1986), Huggett (1993) and Aiyagari (1994) Health risk and precautionary savings: Kotlikoff (1988), Levin (1995), Hubbard, Skinner and Zeldes (1995) and Palumbo (1999). Large scale models with health shocks and health policy: Jeske and Kitao (2009), Pashchenko and Porapakkarm (2013), Janicki (2014), Kopecky and Koreshkova (2014), Capatina (2015)
Related Literature (cont.) 3 Models explaining health spending within Macro frameworks: Lifecycle models that analyze the determinants of rising health care cost in the US Features: technological progress, economic growth and social security (Suen (2006), Hall and Jones (2007), Fonseca et al. (2013) and Zhao (2014)) This paper: extends our previous framework in Jung and Tran (2016) a rich institutional framework and the ACA altering the demographic structure in the model to mimic the process of population aging the effects of aging on health care cost and health financing
The Model: Bewley - Grossman Framework Overlapping Generations (OLG) Model Lifespan: age 20 to 90 Heterogeneous agents Idiosyncratic shocks: labor productivity and health shocks Health as consumption and investment goods Endogenous health spending Choice of private health insurance Market structure: consumption goods, health care goods, capital, labor markets, and incomplete financial markets Fiscal policy: income tax, social security, health insurance, minimum consumption
The Model: Preferences and Technology Preferences: �� � 1 − η � κ � 1 − σ � c η × 1 − l − 1 [ l > 0] ¯ × h 1 − κ l j u ( c , l , h ) = 1 − σ Health capital: Trend Investment Disturbance � �� � � �� � ���� � � φ j m ξ 1 − δ h ǫ h h j = + h j − 1 + j j j � � ϑ, h j , ǫ l Human capital (“labor”): e j = e j Health, labor income and employer insurance shocks: � � � � � � ǫ h j +1 | ǫ h ∈ Π h ǫ l j +1 | ǫ l ∈ Π l ǫ GHI j +1 | ǫ GHI ∈ Π GHI Pr j , Pr j and Pr j ,ϑ j j j
The Model: Health Insurance Arrangements Private health insurance: group (GHI) or individual (IHI) Public (social) health insurance: Medicaid or Medicare Health insurance status: 0 if No insurance, 1 if Individual health insurance IHI, in j = 2 if Group health insurance GHI, 3 if Medicaid.
The Model: Out-of-pocket Health Spending Agent’s out-of-pocket health expenditures depend on insurance state p in j m × m j , if in j = 0 o ( m j ) = � � p in j ρ in j m × m j , if in j > 0
The Model: Technology and Firms Final goods C production sector for price p C = 1: { K , L } { F ( K , L ) − qK − wL } max Medical services M production sector for price p m : { K m , L m } { p m F m ( K m , L m ) − qK m − wL m } max p m is a base price for medical services Price paid by households depends on insurance state: � 1 + ν in j � p in j = p m j ν in j is an insurance state dependent markup factor Profits are redistributed to all surviving agents
The Model: Household Problem t t+1 � � : asset � : asset • • �: permanent income group �: income group • • � : health capital �′ : health capital • • �� : insurance ��′ : insurance • • Shocks: Choices: Shocks: � : health � : consumption � � � � ��� ∶ health • • • � : productivity � : leisure � � � � ��� : productivity • • • � : medical services � � ��� : group HI ��� : group HI � ��� • • • �′ : savings • ��′ : insurance • State vector: Choice = {6, 7, 8, ( � , )+′} " #�3 = {& + 1, (′, ), ℎ′, )+′, ,′ - , ,′ . , ,′ # /01 } " # = {&, (, ), ℎ, )+, , - , , . , , /01 }
Remaining Parts Insurance companies GHI and IHI clear zero profit condition Details Government budget constraint clears Details Pension program financed via payroll tax Details Accidental bequests to surviving individuals Details
A Competitive Equilibrium 1 Given the transition probability matrices and the exogeneous government policies, a competitive equilibrium is a collection of sequences of distributions of household decisions, aggregate capital stocks of physical and human capital, and market prices such that Agents solve the consumer problem The F.O.Cs of firms hold The budget constraints of insurances companies hold All markets clear All government programs and the general budget clear The distribution is stationary Competitive Equilibrium Details
Calibration
Parameterization and Calibration Goal: to match U.S. data pre-ACA (before 2010) Data sources: MEPS: labor supply, health shocks, health expenditures, coinsurance rates PSID: initial asset distribution CMS: demographic profiles Previous studies: income process, labor shocks, aggregates
Health Capital Health capital accumulation: Trend Investment Disturbance � �� � � �� � ���� � � φ j m ξ 1 − δ h ǫ h h j = + h j − 1 + j j j Health capital measure in MEPS: SF 12-v2 Trend � ¯ � �� � � δ h → MEPS|insured & 0-medical spenders → ¯ 1 − δ h h j = h j − 1 j ǫ h and Π h from MEPS
Calibration of Health Shocks MEPS data split each cohort j into 4 risk groups � ¯ � > ¯ j , d > ¯ j , d > ¯ h max h 3 h 2 h 1 Average health capital per risk group: j , d j , d Define shock magnitude: � � ¯ j , d − ¯ ¯ j , d − ¯ ¯ j , d − ¯ h 3 h max h 2 h max h 1 h max j , d j , d j , d ǫ h × h max j = 0 , , , ¯ ¯ ¯ m h max h max h max j , d j , d j , d Assumption: Associate resulting health shock with risk group by age Non-parametric estimation of transition probabilities health shocks Human Capital
Parameterization: Production Function Final goods production: F ( K , L ) = AK α L 1 − α Medical services production: F m ( K m , L m ) = A m K α m m L 1 − α m m Parameters from other studies A = 1 and A m calibrated to match aggregate health spending
Calibration: Price of Medical Services Medicare/Medicaid reimbursement rates (to providers) are about 70% of private HI rates (CMS) Average price markup for uninsured around 60% (Brown (2006)) Large GHI can negotiate favorable prices (Phelps (2003)) Price vector: � � p noIns , p IHI m , p GHI m , p Maid , p Mcare = (1 + [0 . 70 , 0 . 25 , 0 . 10 , 0 . 0 , − 0 . 10]) × p m m m m More Calibration Details
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